A robust detection and localization technique for copy-move forgery in digital images
Image forensic analysis becomes a major role in the field of digital image security due to tampering and forgery. The image forgery violates the authenticity and ownership of digital images. Copy-move forgery considers a significant kind of image forensic analysis algorithm. In this kind, the forger...
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| Format: | Article |
| Language: | English |
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Elsevier
2023-01-01
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| Series: | Journal of King Saud University: Computer and Information Sciences |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S1319157822004323 |
| _version_ | 1797942130645139456 |
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| author | Manaf Mohammed Ali Alhaidery Amir Hossein Taherinia Haider Ismael Shahadi |
| author_facet | Manaf Mohammed Ali Alhaidery Amir Hossein Taherinia Haider Ismael Shahadi |
| author_sort | Manaf Mohammed Ali Alhaidery |
| collection | DOAJ |
| description | Image forensic analysis becomes a major role in the field of digital image security due to tampering and forgery. The image forgery violates the authenticity and ownership of digital images. Copy-move forgery considers a significant kind of image forensic analysis algorithm. In this kind, the forger copies a part of an original image and then pastes it into the selected position from the same image. The purpose of forgery is to hide or highlight a specific region of the original image. To detect copy-move forgery, there are two traditional techniques: block-based and keypoint-based. The main drawback of the keypoint-based technique is the insufficient features for the small and flat regions, which causes undetected forgery. In contrast, the block-based technique has intensive processing. Therefore, this paper proposes a robust scheme that overcomes the drawbacks of the above techniques and maintains their advantages. This scheme adopts three connected stages, the first detects the initial duplicated regions using the SURF-HOG detector and descriptor. Subsequently, the second stage localizes the primary matched regions by SLIC segmentation and then selects the suspicious neighbor regions to be combined with primary regions to obtain the active regions. In the third stage, the block-based technique adopts overlapping Zernike moments to extract sufficient key points from the produced active regions. In the final stage, the duplicated regions are classified into authentic or forged regions. The proposed scheme provides not only forgery detection but also localization and recognition for the duplicated regions. The experimental results show that the proposed scheme is fast and has high accuracy for forgery detection and localization, at least 93.75, and 7.25 in terms of True Positive and False Positive Rates. Moreover, the scheme has high robustness under various conditions and attacks such as geometric transformation attacks and compound photometric attacks. The proposed scheme can be used in sensitive applications such as cybercrime detection and adopted as evidence in the courts. |
| first_indexed | 2024-04-10T20:02:29Z |
| format | Article |
| id | doaj.art-5d607c863a574b0aa081560e23d83a5e |
| institution | Directory Open Access Journal |
| issn | 1319-1578 |
| language | English |
| last_indexed | 2024-04-10T20:02:29Z |
| publishDate | 2023-01-01 |
| publisher | Elsevier |
| record_format | Article |
| series | Journal of King Saud University: Computer and Information Sciences |
| spelling | doaj.art-5d607c863a574b0aa081560e23d83a5e2023-01-27T04:18:49ZengElsevierJournal of King Saud University: Computer and Information Sciences1319-15782023-01-01351449461A robust detection and localization technique for copy-move forgery in digital imagesManaf Mohammed Ali Alhaidery0Amir Hossein Taherinia1Haider Ismael Shahadi2Faculty of Education for Human Sciences, University of Kerbala, Kerbala, IraqFaculty of Engineering, Ferdowsi University of Mashhad, Mashhad, Iran; Corresponding author.Faculty of Engineering, University of Kerbala, Kerbala, IraqImage forensic analysis becomes a major role in the field of digital image security due to tampering and forgery. The image forgery violates the authenticity and ownership of digital images. Copy-move forgery considers a significant kind of image forensic analysis algorithm. In this kind, the forger copies a part of an original image and then pastes it into the selected position from the same image. The purpose of forgery is to hide or highlight a specific region of the original image. To detect copy-move forgery, there are two traditional techniques: block-based and keypoint-based. The main drawback of the keypoint-based technique is the insufficient features for the small and flat regions, which causes undetected forgery. In contrast, the block-based technique has intensive processing. Therefore, this paper proposes a robust scheme that overcomes the drawbacks of the above techniques and maintains their advantages. This scheme adopts three connected stages, the first detects the initial duplicated regions using the SURF-HOG detector and descriptor. Subsequently, the second stage localizes the primary matched regions by SLIC segmentation and then selects the suspicious neighbor regions to be combined with primary regions to obtain the active regions. In the third stage, the block-based technique adopts overlapping Zernike moments to extract sufficient key points from the produced active regions. In the final stage, the duplicated regions are classified into authentic or forged regions. The proposed scheme provides not only forgery detection but also localization and recognition for the duplicated regions. The experimental results show that the proposed scheme is fast and has high accuracy for forgery detection and localization, at least 93.75, and 7.25 in terms of True Positive and False Positive Rates. Moreover, the scheme has high robustness under various conditions and attacks such as geometric transformation attacks and compound photometric attacks. The proposed scheme can be used in sensitive applications such as cybercrime detection and adopted as evidence in the courts.http://www.sciencedirect.com/science/article/pii/S1319157822004323Copy Move Forgery Detection (CMFD)Speed up Robust Feature (SURF)RGMSGray Level Co-occurrence Matrix (GLCM)Zernike moments |
| spellingShingle | Manaf Mohammed Ali Alhaidery Amir Hossein Taherinia Haider Ismael Shahadi A robust detection and localization technique for copy-move forgery in digital images Journal of King Saud University: Computer and Information Sciences Copy Move Forgery Detection (CMFD) Speed up Robust Feature (SURF) RGMS Gray Level Co-occurrence Matrix (GLCM) Zernike moments |
| title | A robust detection and localization technique for copy-move forgery in digital images |
| title_full | A robust detection and localization technique for copy-move forgery in digital images |
| title_fullStr | A robust detection and localization technique for copy-move forgery in digital images |
| title_full_unstemmed | A robust detection and localization technique for copy-move forgery in digital images |
| title_short | A robust detection and localization technique for copy-move forgery in digital images |
| title_sort | robust detection and localization technique for copy move forgery in digital images |
| topic | Copy Move Forgery Detection (CMFD) Speed up Robust Feature (SURF) RGMS Gray Level Co-occurrence Matrix (GLCM) Zernike moments |
| url | http://www.sciencedirect.com/science/article/pii/S1319157822004323 |
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